In the financial services industry, investment banks and financial institutions enter into large numbers of transactions every month that often total in the trillions of dollars. Each of these transactions, which may be completed through money markets, foreign exchanges and derivative markets, to name a few, carries inherent credit, settlement and other financial and transactional risks when settled amongst trading partners. This is an especially large concern for investment banks and financial institutions that enter into thousands of transactions each month. In response, various accounting solutions are utilized in the industry to reduce these financial risks.
One such solution, “netting,” aggregates the transactional settlement value (e.g., cashflows) from multiple transactions, such as outgoing and incoming cashflows from market trades, in order to create a single settlement type payment on a given payscale. Netting may take several forms. Netting by novation, for instance, is where existing obligations are discharged by replacing them with a new obligation. When two trading partners agree to obligation netting, they are legally bound to net amounts from two or more trades due in the same currency for settlement on the same day. Counterparties in foreign exchange transactions, for example, may be required to settle all of the trades included under the agreement by either making or receiving a single payment, thereby reducing the risk by lowering the number and size of payments that would otherwise be needed to settle the underlying transactions. Another type of netting, close-out netting, is an arrangement to settle all contracted, but not currently due, liabilities to and claims on an institution by one single payment immediately upon the occurrence of one of a list of defined events.
Because many of these transactions often involve the same parties, the financial obligations between these common entities may be aggregated to determine a reduced net obligation. By reducing the total number of settlements between the parties, the operational and settlement risks and costs, the cashflows visible in the market, and the credit exposure to the financial institution, may all be reduced.
Despite being a common accounting technique, the implementation of “netting” in the financial services industry has been rudimentary at best. Indeed, the process of netting is typically initiated manually and with elementary computer systems and solutions. For example, many entities implement the netting technique by utilizing one large database that stores all transactional and settlement obligations. A trader or manager may manually traverse and select the particular transactions from the database to group together the transactions for netting. This, as a person of ordinary skill in the art may recognize, can be time consuming and ultimately inefficient as it may often be difficult to determine which transactions to select among tens of thousands of transactions across multiple markets and currencies involving thousands of different entities, subsidiaries and related corporations. Furthermore, the transactions that are netted and the settlements of such transactions are manually recorded. This is especially burdensome and problematic when the settlement values change from day to day, even after settlement.
Furthermore, the current implementations often require the direct manipulation of the cashflow and/or transaction data within the database, effecting the entities' obligations to track its records for audit and disclosure purposes. As a result, transactional and netting records, if they are kept in the first place at all, are often lost over time as the data is modified in response to changing market conditions and transactions.
While the use of a computer database allows a person to access the data of the transaction, it may, nonetheless, be difficult to find the particular transaction that would benefit the company and reduce financial risks through netting. This is especially difficult in the face of tens of thousands of transactions, each containing variables and settlement requirements that change often.
With the fast-changing nature of day-to-day trades and other transactions, there is, accordingly, a need to dynamically determine the transactions that should be netted and to determine the net-position of any number of transactions (i.e., how much is owed, or is to be paid, when it is time to settle), even when settlement values change. Furthermore, there is a need to dynamically keep a recorded trail of netting related actions.